Tech Talk Toe: An afternoon with the Chennai School of AI

What do you get when you have four machine learning & AI experts, a room full of enthusiastic coders and some pretty cool tech? An afternoon of hands-on learning and stimulating conversation of course!

On the 24th of November, Crayon Data hosted the Chennai School of AI Meetup #2. The afternoon saw more than 60 people turn up in attendance for 4 sessions. Before the event was off to a start, the room was filled with bright, young and keen people. And the best part? About 70% of them were students, eager and passionate for more information on machine learning. And they weren’t disappointed. The content covered in these sessions by the 4 different speakers provided the perfect fodder!

The first session was an introduction to machine learning and natural language processing. The speaker, Satyadev is a data scientist from Chennai-based AI firm – Mad Street Den, who set the perfect tone for the meet-up. He started the session with a well-known topic – normal distribution. And soon got into the specifics of it. The session gave us a clear picture on the process of choosing a model. Including all the parameters that completely depend on what business case one is trying to solve. He also explained why ‘one-size-fits-all’ models do not work. In the process of laying down the foundation on what machine learning actually is, he also busted some of the common myths we all believed.

The second session on Multi-Label Classification was held by Crayon’s own Sundara Raman. He started out by explaining the differences between Multi-class classification and Multi-label classification. He then proceeded to brief us on Natural Language Processing (NLP) and Bidirectional LSTM – how past events help predict future ones. He further touched upon TF-IDF (Term Frequency-Inverse Document Frequency) where TF reflects the number of times a word occurs in a single document and IDF reflects the number of times the word occurs in different documents. Finally, he explained the importance of preprocessing and hyperparameter tuning to increase model accuracy.

After a quick break for snacks and tea, Vishal Gupta conducted the third session on the methodologies of creating Portmanteaus using LSTM. A student himself, Vishal talked about the limitations of traditional neural networks. The major drawback of a traditional neural network is their inability to remember. Hence, they lack context, which is why they find it difficult to use reasoning to predict future events from past ones. He then explained that recurrent neural networks (RNN) address this issue. They have loops in them, allowing information to persist. However, one of the drawbacks of RNNs is “long-term dependencies”. As the gap grows, RNNs find it difficult to connect the past information. But the Long Short-Term Memory (LSTM) is a special kind of RNN is capable of learning “long-term dependencies”. Afterwards, he briefly took the audience through the working of LSTM and how it decides what information to forget, what new information to store and how much it needs to update and how much to forget. He ended his long session with a demo of a Portmanteaus using an LSTM model that he had built.

The final speaker was Gaurav G Punjabi from Coffee. Gaurav’s topic was predominantly focused on the workings of chatbots. Yeah, that’s right. Chatbots are those beloved bots we frequently encounter when businesses want to assist their customers. The session revolved around how to build a conversational AI using the RASA stack – an open source tool to build contextual AI assistants. Gaurav talked about how RNNs help chatbots maintain context while having conversations with users. Then he focused on building a language understanding model with RASA NLU for a chatbot to understand regular sentences from natural human language. At the end of the session, he showcased a simple chatbot that was built using RASA.

Once all the four sessions were done, the attendees, organizers and speakers lingered at the Crayon office for questions, discussions and to network with like-minded people! On the whole, the Chennai School of AI Meetup #2 was a great opportunity to learn and discuss cutting-edge technology. The first of many more such meetups that’ll take place in the Crayon box, it’s the start to growing an ML and AI community in Chennai.